Uploaded September 2025 | Updated September 2026, 2 hours ago
(Neha) Networks have in recent years emerged as an invaluable tool for describing and quantifying complex systems in many branches of science. Recent studies suggest that networks often exhibit hierarchical organization, where vertices divide into groups that further subdivide into groups of groups, and so forth over multiple scales. Here we present a general technique for inferring hierarchical structure from network data and demonstrate that the existence of hierarchy can simultaneously explain and quantitatively reproduce many commonly observed topological properties of networks, such as right-skewed degree distributions, high clustering coefficients, and short path lengths. We further show that knowledge of hierarchical structure can be used to predict missing connections in partially known networks with high accuracy, and for more general network structures than competing techniques. Taken together, our results suggest that hierarchy is a central organizing principle of complex networks, capable of offering insight into many network phenomena.
pretalx.com/pycon-au-2025/talk/8PM8L9
python, pycon, australia, programming, conference, technical, developers, panel, sessions, libraries, frameworks, community, sysadmins, students, education, data, science
Videos licensed as CC-BY-NC-SA 4.0
PyCon AU is the national conference for the Python programming community, bringing together professional, student and enthusiast developers, sysadmins and operations folk, students, educators, scientists, statisticians, and many others besides, all with a love for working with Python.
Licensed as CC BY-NC-SA - creativecommons.org/licenses/by-nc-sa/4.0
Produced by Next Day Video Australia: https://nextdayvideo.com.au
Fri Sep 12 12:20:00 2025 at Ballroom 1
(Neha) Networks have in recent years emerged as an invaluable tool for describing and quantifying complex systems in many branches of science. Recent studies suggest that networks often exhibit hierarchical organization, where vertices divide into groups that further subdivide into groups of groups, and so forth over multiple scales. Here we present a general technique for inferring hierarchical structure from network data and demonstrate that the existence of hierarchy can simultaneously explain and quantitatively reproduce many commonly observed topological properties of networks, such as right-skewed degree distributions, high clustering coefficients, and short path lengths. We further show that knowledge of hierarchical structure can be used to predict missing connections in partially known networks with high accuracy, and for more general network structures than competing techniques. Taken together, our results suggest that hierarchy is a central organizing principle of complex networks, capable of offering insight into many network phenomena.
pretalx.com/pycon-au-2025/talk/8PM8L9
python, pycon, australia, programming, conference, technical, developers, panel, sessions, libraries, frameworks, community, sysadmins, students, education, data, science
Videos licensed as CC-BY-NC-SA 4.0
PyCon AU is the national conference for the Python programming community, bringing together professional, student and enthusiast developers, sysadmins and operations folk, students, educators, scientists, statisticians, and many others besides, all with a love for working with Python.
Licensed as CC BY-NC-SA - creativecommons.org/licenses/by-nc-sa/4.0
Produced by Next Day Video Australia: https://nextdayvideo.com.au
Fri Sep 12 12:20:00 2025 at Ballroom 1
